Artem Keydunov: prediction

Transcript context

…So before we go to the lightning round, I wanted to ask you on your thoughts on embedded analytics and in a sense, the kind of chatbots that people are inserting on their websites and building with LLMs is very much sort of end user programming or end user interaction with their own data. I love seeing embedded analytics, and for those who don't know, embedded analytics is basically user facing dashboards where you can see your own data, right? Instead of the company seeing data across all their customers, it's an individual user seeing their own data as a slice of the overall data that is owned by the platform that they're using. So I love embedded analytics. Well, actually, overwhelmingly, the observation that I've had is that people who try to build in this market fail to monetize. And I was wondering your insights on why. I think overall, the statement is true. It's really hard to monetize, you know, like in embedded analytics. That's why at Qube we're excited more about our internal kind of BI use case, or like a company's a building, you know, like a chatbots for their internal data consumption or like internal workflows. Embedded analytics is hard to monetize because it's historically been dominated by the BI vendors. And we still see a lot of organizations are using BI tools as vendors. And what I was talking about, BI vendors adding natural language interfaces, they will probably add that to the embedded analytics capabilities as well, right? So they would be able to embed that too. So I think that's part of it. Also, you know, if you look at the embedded analytics market, the bigger organizations are big GADs, they're really more custom, you know, like it becomes and at some point I see many organizations, they just stop using any vendor, and they just kind of build most of the stuff from scratch, which probably, you know, like the right way to do. So it's sort of, you know, like you got a market that is very kept at the top. And then you also in that middle and small segment, you got a lot of vendors trying to, you know, like to compete for the buyers. And because again, the BI is very fragmented, embedded analytics, therefore is fragmented also. So you're really going after the mid market slice, and then with a lot of other vendors competing for that. So that's why it's historically been hard to monetize, right? I don't think AI really going to change that just because it's using model, you just pay to open AI. And that's it, like everyone can do that, right? So it's not much of a competitive advantage. So it's going to be more like a commodity features that a lot of vendors would be able to leverage. This is great, Artem. As usual, we got our lightning round. So it's three questions. One is about acceleration, one on exploration, and then take away. The acceleration thing is what's something that already happened in AI or maybe, you know, in data that you thought would take much longer, but it's already happening today.…

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